Articles

Generative artificial intelligence has moved from the periphery to the core of educational technology discourse, positioning higher education at a decisive juncture rather than one of passive observation. This synthesis of emerging literature on tools such as ChatGPT examines how integration within teaching, learning, and administration generates transformative potential alongside substantial disruption. Drawing upon recent scholarship across pedagogical innovation, assessment design, and institutional governance, the analysis organizes findings around three central axes. These address the capacity of generative AI to personalize learning experiences and alleviate administrative burdens, the threats posed to academic integrity and the cultivation of independent critical thought, and the uneven institutional readiness to formulate coherent policy responses (Shiri, 2023; KAHYAOĞLU ERDOĞMUŞ, 2024; Bhatt, 2024). A landscape defined less by the technology itself and more by institutional choices regarding its application emerges from the synthesis. On the opportunity side, generative AI can scaffold student writing, provide immediate feedback mechanisms, and liberate faculty from routine tasks; however, these gains rely on deliberate pedagogical design rather than mere tool adoption (Herbert, 2024; Silva, 2020; Bakar, 2024). Conversely, on the risk side, conventional plagiarism detection has proven inadequate against AI-generated text, and the ease of content production threatens to erode the habits of drafting, revising, and intellectual struggle that constitute genuine learning (Mendoza, 2024; al Qahtani et al., 2024; Rao, 2024). Further examination indicates that institutional responses remain fragmented, ranging from outright prohibition to uncritical embrace, with only a minority adopting the nuanced, discipline-specific policies suggested by the evidence (Lin, 2024; Dumouchel, 2024). The paper concludes by proposing a framework for institutional policy that treats AI literacy as a core competency rather than a supplementary concern, embeds ethical considerations into the program-level curriculum, and distinguishes between contexts where generative AI supports learning and those where it undermines it (Sangwa, 2024; Akram, 2024; Bloxham et al., 2024). Future research should advance beyond attitudinal surveys toward longitudinal studies of learning outcomes and comparative analyses of policy effectiveness across institutional types (Meakin, 2024; Madsen, 2024; Khrisat, 2024). The central argument posits that generative AI neither promises salvation nor portends ruin; its consequences will be determined by the intentionality with which educators and administrators respond.